Adaptive image-based visual servoing of wheeled mobile robots with fixed camera configuration

In this paper, we will study the uncalibrated vision-based positioning problem of wheeled mobile robots by using a ceiling-mounted camera. A new image-based visual servoing scheme will be proposed, which can cope with the unknown intrinsic and extrinsic parameters of the camera and the uncertain distance parameter of the feature point from geometric center of the mobile robot. The presented approach is developed via extending the depth-independent interaction matrix framework for robot manipulators to mobile robots such that the nonlinear dependence on unknown parameters can be removed from the image-Jacobian matrix and then, we can linearly parameterize uncertain parameters in the closed-loop system. In this way, an estimation scheme for the online updating of uncertain parameters can be developed very efficiently. To show that image errors can be guaranteed to be asymptotically convergent, stability analysis will be carried out by using Lyapunov theory. To validate the performance of the presented approach, simulation and experimental results will also be provided.